Inversion of fuzzy neural networks for the reduction of noise in the control loop
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Inversion of fuzzy neural networks for the reduction of noise in the control loop. / Nentwig, M.; Mercorelli, Paolo.
Intelligent Manufacturing Systems. Hrsg. / Carlos Eduardo Pereira; Oleg Zaikin; Zbigniew A. Banaszak. Band 9 International Federation of Automatic Control, 2008. S. 157-162 (IFAC Proceedings Volumes; Band 41, Nr. 3).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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TY - CHAP
T1 - Inversion of fuzzy neural networks for the reduction of noise in the control loop
AU - Nentwig, M.
AU - Mercorelli, Paolo
N1 - Conference code: 9
PY - 2008
Y1 - 2008
N2 - A robust throttle valve control has always been a attractive problem since throttle by wire systems were established in the mid-nineties. Often in control strategy, a feedforward controller is adopted in which an inverse model is used. Mathematical inversions of models imply a high order of differentiation of the state variables and consequently noise effects. In general, neural networks are a very effective and popular tool mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the control problem schemes. This paper presents a control strategy based upon an inversion of a feed forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented in which two control loops are explicitly compared
AB - A robust throttle valve control has always been a attractive problem since throttle by wire systems were established in the mid-nineties. Often in control strategy, a feedforward controller is adopted in which an inverse model is used. Mathematical inversions of models imply a high order of differentiation of the state variables and consequently noise effects. In general, neural networks are a very effective and popular tool mostly used for modeling. The inversion of a neural network produces real possibilities to involve the networks in the control problem schemes. This paper presents a control strategy based upon an inversion of a feed forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. Simulated results from real data measurements are presented in which two control loops are explicitly compared
KW - Engineering
KW - Fuzzy networks
KW - inversion
KW - noise reduction
U2 - 10.3182/20081205-2-CL-4009.00029
DO - 10.3182/20081205-2-CL-4009.00029
M3 - Article in conference proceedings
SN - 978-3-902661-40-1
VL - 9
T3 - IFAC Proceedings Volumes
SP - 157
EP - 162
BT - Intelligent Manufacturing Systems
A2 - Pereira, Carlos Eduardo
A2 - Zaikin, Oleg
A2 - Banaszak, Zbigniew A.
PB - International Federation of Automatic Control
T2 - 9th International Federation on Automatic Control Conference on Intelligent Manufacturing Systems - 2008
Y2 - 9 October 2008 through 10 October 2008
ER -